2027 Summer Analyst Program - Insurance Risk - Data Science

Public source summary from intern-list.com / Jobright.

KKR is a global investment firm offering alternative asset management, capital markets, and insurance solutions. The 2027 Summer Analyst will join the Insurance Data Science group within the Liability Risk business, developing machine learning and AI solutions, predictive models, data analytics, and automated data pipelines for insurance risk and financial applications.

Responsibilities

Implement machine learning and optimization tools Develop supervised and unsupervised machine learning models Build AI solutions for the team and the wider firm Assist with ad hoc data analytics projects Collaborate to develop the team’s automated data pipeline

Qualifications: Anticipated graduation date from a master's program in December 2027 - June 2028 Area of study in quantitative discipline such as Computer Science, Engineering, Mathematics, Actuarial Science, or related technical fields Background in a technical or scientific field and at least three years/six semesters of programming experience Proficiency in Python and SQL is required, along with extensive understanding of data structures, statistics, regression, and core machine learning methods Knowledge of Generative AI and modern LLM tooling is required - e.g. building RAG pipelines with vector search, agentic workflows, and tool/function calling (MCP-based integrations) Ability to critically evaluate AI-generated outputs for accuracy and relevance is required Comfort using AI tools to improve productivity and quality of work is required Strong analytical, organizational, and communication (written and verbal) skills Proactive, detail oriented, and deadline driven; possess excellent documentation Exposure to loop engineering, structured outputs, and evaluating LLM systems is valued

Benefits: Employees may be eligible for a discretionary bonus, based on factors such as individual and team performance. Following the conclusion of the internship, 2028 full-time offers may be extended to exceptional performers.